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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

Architecture of HDFS Federation

The crux of the HDFS Federation feature is that it allows for multiple NameNodes to run on a cluster. These NameNodes are independent and do not have any dependency on each other. However, the DataNodes are shared between all the NameNodes in the system. The NameNodes are said to be federated because they can be run independently without coordination.

Each DataNode sends heartbeats and block report information to all the NameNodes in the cluster. DataNodes also receive instructions from all the NameNodes. They are the common shared storage resource in the cluster and still run on commodity hardware. However, they cater to different NameNodes, and in turn, facilitate different Namespaces. These independent Namespaces provide isolation guarantees in a multitenant environment. By running many NameNodes, the cluster can be horizontally scaled and requests can be load-balanced among these NameNodes.

The following diagram shows the architecture of a federated HDFS...

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